26

2019-11-25-climate.R

@@ -1,14 +1,14 @@
 library(sf)
+library(albersusa) # hrbrmstr/albersusa
+library(rnaturalearth)
 library(hrbrthemes)
 library(tidyverse)
 
-#https://www.ncdc.noaa.gov/ibtracs/
-
 st_read(here::here("data/me-counties.json")) %>%
   st_set_crs(4326) %>%
   st_transform(albersusa::us_laea_proj) -> maine
 
-rnaturalearth::ne_states("united states of america", returnclass = "sf") %>%
+ne_states("united states of america", returnclass = "sf") %>%
   filter(!(postal %in% c("AK", "HI"))) %>%
   st_transform(albersusa::us_laea_proj) -> states
 
@@ -85,10 +85,8 @@ ggplot() +
     gb,
     xmin = -2031896.9,
     xmax =  7725851.8,
-    ymin =  2150000.0, # #732581.2,
+    ymin =  2150000.0,
     ymax =  5685229.4
-    # ymin =  1500000.0, # #732581.2,
-    # ymax =  4685229.4
   ) +
   geom_sf(data = states, color = "white", fill = "#3B454A", size = 0.0725) +
   geom_sf(data = maine, size = 0.125) +
@@ -108,9 +106,3 @@ ggplot() +
   theme(legend.direction = "horizontal") +
   theme(legend.key.width = unit(2, "lines")) +
   theme(legend.title = element_text(hjust = 1))
-
-
-
-
-
-

2019-11-26-hydrology.R

@@ -0,0 +1,77 @@
+library(sf)
+library(tigris)
+library(hrbrthemes)
+library(tidyverse)
+
+c(
+  "#366cff", "#4476ff", "#517fff", "#5f89ff", "#6c93ff", "#799dff", "#87a7ff", "#94b1ff",
+  "#a1baff", "#afc4ff", "#bcceff", "#cad8ff", "#d7e2ff", "#e4ebff", "#f2f5ff", "#ffffff"
+) -> pal
+
+st_read(here::here("data/me-counties.json"), stringsAsFactors = FALSE) %>%
+  st_set_crs(4326) -> me_counties
+
+pull(me_counties, NAME) %>%
+  unique() %>%
+  map(~area_water(state = "Maine", county = .x, class = "sf") %>%
+        mutate(county = .x)) %>%
+  do.call(rbind, .) -> me_aw
+
+pull(me_counties, NAME) %>%
+  unique() %>%
+  map(~linear_water(state = "Maine", county = .x, class = "sf") %>%
+        mutate(county = .x)) %>%
+  do.call(rbind, .) -> me_rv
+
+me_rv %>%
+  mutate(
+    sz = ifelse(grepl("(River|Rive|Riv)$", FULLNAME), 0.25, 0.04)
+  ) -> me_rv
+
+ggplot() +
+  geom_sf(data = st_union(me_counties), fill = "#04005e", color = NA) +
+  geom_sf(data = me_aw, size = 0, fill = "white", color = NA, show.legend = FALSE) +
+  geom_sf(data = me_rv, aes(size = I(sz)), color = "white", fill = NA, show.legend = FALSE) +
+  coord_sf(datum = NA) +
+  labs(
+    title = "Maine Hydrology"
+  ) +
+  theme_ipsum_es(grid="") +
+  theme(plot.title = element_text(color = "white")) +
+  theme(plot.background = element_rect(color = "black", fill = "black")) +
+  theme(panel.background = element_rect(color = "black", fill = "black"))
+
+
+ggplot() +
+  geom_sf(data = st_union(me_counties), fill = "#04005e", color = NA) +
+  geom_sf(data = me_aw, size = 0, fill = "white", color = NA, show.legend = FALSE) +
+  geom_sf(data = me_rv, aes(size = I(sz)), color = "white", fill = NA, show.legend = FALSE) +
+  coord_sf(datum = NA) +
+  labs(
+    title = "Maine Hydrology",
+    caption = "Data: {tigris} • <git.rud.is/hrbrmstr/y2019-30daymapchallenge> • #30DayMapChallenge"
+  ) +
+  theme_ipsum_es(grid="") +
+  theme(plot.title = element_text(hjust = 0.5))
+
+# vern <- st_read("~/Desktop/Maine_Significant_Vernal_Pools/Maine_Significant_Vernal_Pools.shp", stringsAsFactors=FALSE)
+#
+# st_intersection(vern, st_transform(me_counties, st_crs(vern))) %>%
+#   filter(NAME == "York") -> yc_vern
+#
+# ggplot() +
+#   geom_sf(data = yc_vern[10,], color = NA, fill = "white") +
+#   coord_sf(datum = NA) +
+#   theme_ipsum_es(grid="") +
+#   theme(plot.background = element_rect(color = "black", fill = "black")) +
+#   theme(panel.background = element_rect(color = "black", fill = "black"))
+#
+#
+
+unique(as.character(me_rv$FULLNAME)) %>%
+  stringi::stri_match_last_regex(" ([[:alpha:]]+)$") %>%
+  .[,2] %>%
+  unique() %>% sort()
+
+
+